Cognitive Management and Orchestration of Resources in the Edge Cloud Continuum - White Paper v1.1

Modern organizations increasingly deploy applications across the so-called Edge-Cloud
continuum. Such deployment requires a high degree of human intervention. Furthermore, the
management of applications during runtime also requires heavy configuration. To automate
this process, there are today several tools that manage (orchestrate) the deployment and
running of applications. Still, with the increasing trend to bring applications, services, and
processes closer to data sources (far Edge), there is a growing need to have an efficient and
flexible orchestration of resources from the far Edge to Cloud.

This white paper provides an overview and a comparative analysis of cognitive and intelligent
resource management techniques for the Edge-Cloud continuum, which are developed in six
European research and innovation projects: CODECO, COGNIFOG, COGNIT, MLSysOps,
ENACT, and DECICE. These projects address the growing complexity of managing distributed
computing resources across Cloud and Edge environments. In this direction they develop
advanced AI-driven approaches to optimizing performance, scalability, and security.

The document emphasizes the role of cognitive techniques, such as Machine Learning (ML)
and Artificial Intelligence (AI), in automating resource allocation, workload distribution, and
system adaptation in real-time. These technologies are essential for managing heterogeneous
environments that span from IoT devices at the Edge to centralized Cloud data centres.
Key challenges in this domain include ensuring reliable network connectivity, protecting data
privacy, managing heterogeneous resources, and scaling deployments efficiently. Each of the
projects discussed in this paper offers a unique approach and solution to these challenges.